SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q9Y704 from www.uniprot.org...

The NucPred score for your sequence is 0.59 (see score help below)

   1  MNIKKKSFLFQFLFGWIVLSSAQWLSVLDEAENLNSSFSLESVDSFAPVR    50
  51  PRFIIDEDFAEDYNLTVDILHRPLQENFDSFFPNVEAYVESGNSNGDLMS   100
 101  DNGKLDDLNSRAAYSALKALQNSYGSSHLYRFTPYELFGQSIWIEEAPEV   150
 151  NHVGWSIMFDNLGRYFLLELRGLREVTFALFITFSIVPIITGILTVYIYK   200
 201  KKYCVIKFNKSGRSKKKDSWLKRSKDELLRTDSANLLTLNDNDEPVMIRH   250
 251  SCKRTCILFATLEYNIPEWNIKIKIGGLGVMAELMSKTLKQYDLVWVVPC   300
 301  VGDITYPVAETAPSLVVKVVNQDYEVKVFYHYKDNIKYVLLDSPIFRKRT   350
 351  SHDPYPPRMDDISSAIFYSVWNQSIAAIIRREKVDIYHINDYHGALAPIY   400
 401  NLPEVIPCAISLHNAEFQGLWPLQSSIDEREVCGLFNVSKTICREYIQFG   450
 451  NAFNLMHCGVSYVRRHQSGYGVVGVSNKYGQRSWVRYPVFWSLKKIGQLP   500
 501  NPDPTDIGLSVNPVNQQLPDFAEYASVRKENKRKAQEWAGLTIDDEADLL   550
 551  VFVGRWSVQKGIDILADLAPTLLEKFNIQLIVVGPLIDLYGKFAAEKFMY   600
 601  IMERYPGRVFSKPEFVHLPPFIFEGADFALIPSRDEPFGLVAVEFGRRGA   650
 651  ICIGSRVGGLGEMPGWWYSVESSSTAYLLKQLEKSCTLALKSTPEMRHKL   700
 701  RIAALQQRFPVDEWVALYDRLIRNCIKAHNKQQQRRSIKSFFSCITPNKP   750
 751  TKDVNDILSEKSAFSPADYEHSIDIREHTSYDANSMDNDSDEDNYEQAES   800
 801  IISSLSSSALSELSYISESSMNIGSRLDERFIDANGVAIRDFSAELTYLT   850
 851  PENSKGKLSIDHFLNKVQSRWHDEEHHYYKTGFRKRVYKYLKIKDKKSKD   900
 901  VDPDDDLVNQLPLNAYTKPRYKSAASTRLNIYQRILYLKVFTWPLYTIFL   950
 951  SLGQILSISSFQLSLLSGFEDNNQISLYVITGVFILSTIVWWGLYRNLPS  1000
1001  VHSLSLPFAVYALAFLFTGISSMSLPYHIRGWLSYAATWVYAIAAASGPL  1050
1051  YFTLNFEDEHCSGLGSSITRACVLQGVQQLWLSFLWLWGTLSSRLDYNYK  1100
1101  VLLQPINSVYVVAGVWPVSFVLLSVCILLYKGLPPFYRQKPGSIPAFSKS  1150
1151  LLHRKVVICFLISVINQNFWMSTLISQAWRFFWGSKLTKLWKIVVMTVSF  1200
1201  LVGAWLIIFYVLRKLSNKHTWMVPVLGLGFGAIKWMHVFWGTSNVGIFLP  1250
1251  WAGIAGPYLSRALWLWLGILDSIQGIGNGLILLQTLSRRHVTNTLMISQL  1300
1301  AGSATSILARFVSPTKTGPANVFPDLTGYTPVDRAKPVANAPFWICLILN  1350
1351  VALCIMYLRCYHRENISRP                                 1369

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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